CIL Theory Overview
Simon Points
- reparametrization-trick
- pooling-layer
- non-negative-matrix-factorization
- mixture-models
- k-means-model
- gradient-descent
- glove-model
- gaussian-mixture-models
- evidence-lower-bound
- activation-functions
- expectation-maximization-algorightm
- maximum-likelihood-estimation
- probabilistic-latent-semantic-analysis
- normal-distribution
- lagrange-multipliers
- l-smoothness
- jensen-inequality
- frobenius-norm
- variance-covariance-matrix
- singular-value
- nuclear-norm-minimization
- hadamard-product
- fenchel-conjugate
- eigenvector
- eigenvalue
- eigen-decomposition
- dimension-reduction
- covariance-matrix
- cil-shrink-operator
- cil-reconstruction-theorem
- cil-randomized-algorithm-svd
- characteristic-polynomial
- nuclear-norm
- frobenius-norm
- cil-theory-overview
- cil-important-points
- 03-05-np-hard
- 03-04-svd-with-imputation
- 03-03-svd-matrix-completion
- 03-02-svd-pca
- 03-01-eckart-young-theorem
- 03-00-singular-value-decomposition
- 02-09-fully-observed-rank-one-model
- 02-08-gradient-dynamics
- 02-07-gradients
- 02-06-convextiy-definition
- 02-05-rank-one-model
- 02-04-preprocessing-normalization
- 02-03-netflix-data
- 02-02-collaborative-filtering
- 02-01-recommender-systems
- 02-00-matrix-approximation
- 01-00-dimension-reduction